Overview

Dataset statistics

Number of variables15
Number of observations30000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 MiB
Average record size in memory120.0 B

Variable types

Numeric14
Categorical1

Alerts

Iabc is highly overall correlated with Vdc and 1 other fieldsHigh correlation
Ipv is highly overall correlated with VpvHigh correlation
Vdc is highly overall correlated with IabcHigh correlation
Vpv is highly overall correlated with Iabc and 1 other fieldsHigh correlation
ia is highly overall correlated with vaHigh correlation
ib is highly overall correlated with vbHigh correlation
ic is highly overall correlated with vcHigh correlation
va is highly overall correlated with iaHigh correlation
vb is highly overall correlated with ibHigh correlation
vc is highly overall correlated with icHigh correlation
Vabc is highly skewed (γ1 = -21.58082596)Skewed
ib has 566 (1.9%) zerosZeros

Reproduction

Analysis started2024-04-16 09:19:31.176789
Analysis finished2024-04-16 09:20:11.498954
Duration40.32 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

Time
Real number (ℝ)

Distinct29994
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6257812
Minimum2.5307124 × 10-5
Maximum14.369075
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-04-16T14:50:11.812728image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum2.5307124 × 10-5
5-th percentile0.67405621
Q13.2532569
median6.5015752
Q39.8213283
95-th percentile13.105432
Maximum14.369075
Range14.36905
Interquartile range (IQR)6.5680714

Descriptive statistics

Standard deviation3.9326047
Coefficient of variation (CV)0.59353072
Kurtosis-1.1111392
Mean6.6257812
Median Absolute Deviation (MAD)3.2838389
Skewness0.11488697
Sum198773.44
Variance15.46538
MonotonicityNot monotonic
2024-04-16T14:50:12.063978image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.731160137 2
 
< 0.1%
8.366301204 2
 
< 0.1%
8.413296504 2
 
< 0.1%
0.973140227 2
 
< 0.1%
1.876931222 2
 
< 0.1%
9.959349751 2
 
< 0.1%
3.54757434 1
 
< 0.1%
5.909089158 1
 
< 0.1%
13.01522336 1
 
< 0.1%
11.51322152 1
 
< 0.1%
Other values (29984) 29984
99.9%
ValueCountFrequency (%)
2.530712379 × 10-51
< 0.1%
2.817800145 × 10-51
< 0.1%
5.932365172 × 10-51
< 0.1%
0.003358926861 1
< 0.1%
0.003422267982 1
< 0.1%
0.003428071319 1
< 0.1%
0.003440449229 1
< 0.1%
0.003537220386 1
< 0.1%
0.003537513632 1
< 0.1%
0.003540446092 1
< 0.1%
ValueCountFrequency (%)
14.36907496 1
< 0.1%
14.36787499 1
< 0.1%
14.3673753 1
< 0.1%
14.36197576 1
< 0.1%
14.3609758 1
< 0.1%
14.35777619 1
< 0.1%
14.35487657 1
< 0.1%
14.35177667 1
< 0.1%
14.35157668 1
< 0.1%
14.3507767 1
< 0.1%

Ipv
Real number (ℝ)

HIGH CORRELATION 

Distinct1355
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7576519
Minimum0.7180481
Maximum3.0614014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-04-16T14:50:12.333983image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.7180481
5-th percentile1.3424377
Q11.431366
median1.5174561
Q32.23172
95-th percentile2.5722961
Maximum3.0614014
Range2.3433533
Interquartile range (IQR)0.800354

Descriptive statistics

Standard deviation0.43488128
Coefficient of variation (CV)0.24742173
Kurtosis-1.0830675
Mean1.7576519
Median Absolute Deviation (MAD)0.12203979
Skewness0.75871248
Sum52729.557
Variance0.18912172
MonotonicityNot monotonic
2024-04-16T14:50:12.581226image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.478668213 112
 
0.4%
1.471099854 105
 
0.4%
1.463531494 100
 
0.3%
1.425689697 99
 
0.3%
1.497589111 99
 
0.3%
1.493804932 99
 
0.3%
1.455963135 98
 
0.3%
1.459747314 98
 
0.3%
1.466369629 97
 
0.3%
1.482452393 97
 
0.3%
Other values (1345) 28996
96.7%
ValueCountFrequency (%)
0.7180480957 1
< 0.1%
0.7199401855 1
< 0.1%
0.7218322754 1
< 0.1%
0.7369689941 1
< 0.1%
0.7644042969 1
< 0.1%
0.7890014648 1
< 0.1%
0.9034729004 1
< 0.1%
0.9252319336 1
< 0.1%
0.932800293 1
< 0.1%
0.9857788086 1
< 0.1%
ValueCountFrequency (%)
3.061401367 1
< 0.1%
3.056671143 1
< 0.1%
3.053833008 1
< 0.1%
3.044372559 1
< 0.1%
3.043426514 1
< 0.1%
3.039642334 1
< 0.1%
3.034912109 1
< 0.1%
3.03112793 1
< 0.1%
3.024505615 1
< 0.1%
3.018829346 1
< 0.1%

Vpv
Real number (ℝ)

HIGH CORRELATION 

Distinct1673
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.976542
Minimum1.1169434
Maximum106.30493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-04-16T14:50:12.835094image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.1169434
5-th percentile3.3444214
Q190.490723
median101.20239
Q3101.63574
95-th percentile102.05109
Maximum106.30493
Range105.18799
Interquartile range (IQR)11.14502

Descriptive statistics

Standard deviation23.871453
Coefficient of variation (CV)0.25953849
Kurtosis9.4007122
Mean91.976542
Median Absolute Deviation (MAD)0.61035156
Skewness-3.2790805
Sum2759296.3
Variance569.84625
MonotonicityNot monotonic
2024-04-16T14:50:13.114604image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101.4099121 144
 
0.5%
101.2634277 134
 
0.4%
101.2878418 128
 
0.4%
2.545166016 127
 
0.4%
101.5563965 126
 
0.4%
101.2817383 126
 
0.4%
101.776123 125
 
0.4%
101.348877 125
 
0.4%
101.8066406 125
 
0.4%
101.4587402 124
 
0.4%
Other values (1663) 28716
95.7%
ValueCountFrequency (%)
1.116943359 1
< 0.1%
1.708984375 1
< 0.1%
1.794433594 1
< 0.1%
1.824951172 1
< 0.1%
1.928710938 1
< 0.1%
1.947021484 1
< 0.1%
1.953125 1
< 0.1%
2.008056641 1
< 0.1%
2.026367188 1
< 0.1%
2.081298828 1
< 0.1%
ValueCountFrequency (%)
106.3049316 1
< 0.1%
106.072998 1
< 0.1%
105.9387207 1
< 0.1%
105.9020996 1
< 0.1%
105.8654785 1
< 0.1%
105.847168 1
< 0.1%
105.2612305 1
< 0.1%
104.9621582 1
< 0.1%
104.5288086 2
< 0.1%
104.4067383 1
< 0.1%

Vdc
Real number (ℝ)

HIGH CORRELATION 

Distinct218
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.07679
Minimum0.5859375
Maximum237.89062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-04-16T14:50:13.397120image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.5859375
5-th percentile2.0507812
Q1142.96875
median143.84766
Q3146.77734
95-th percentile148.53516
Maximum237.89062
Range237.30469
Interquartile range (IQR)3.8085938

Descriptive statistics

Standard deviation37.592898
Coefficient of variation (CV)0.274247
Kurtosis8.5982022
Mean137.07679
Median Absolute Deviation (MAD)1.4648438
Skewness-2.6804789
Sum4112303.6
Variance1413.226
MonotonicityNot monotonic
2024-04-16T14:50:13.664423image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
143.5546875 2603
 
8.7%
143.8476562 2468
 
8.2%
143.2617188 2458
 
8.2%
144.140625 1921
 
6.4%
142.96875 1800
 
6.0%
144.4335938 1294
 
4.3%
1.171875 1154
 
3.8%
142.6757812 1112
 
3.7%
147.0703125 1023
 
3.4%
147.3632812 1021
 
3.4%
Other values (208) 13146
43.8%
ValueCountFrequency (%)
0.5859375 1
 
< 0.1%
0.87890625 8
 
< 0.1%
1.171875 1154
3.8%
1.46484375 117
 
0.4%
1.7578125 178
 
0.6%
2.05078125 160
 
0.5%
2.34375 208
 
0.7%
2.63671875 38
 
0.1%
2.9296875 3
 
< 0.1%
3.22265625 6
 
< 0.1%
ValueCountFrequency (%)
237.890625 1
 
< 0.1%
237.5976562 1
 
< 0.1%
237.3046875 3
< 0.1%
237.0117188 3
< 0.1%
236.71875 1
 
< 0.1%
236.4257812 4
< 0.1%
236.1328125 1
 
< 0.1%
235.8398438 3
< 0.1%
235.546875 7
< 0.1%
235.2539062 3
< 0.1%

ia
Real number (ℝ)

HIGH CORRELATION 

Distinct720
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.022878967
Minimum-6.3588877
Maximum11.271728
Zeros0
Zeros (%)0.0%
Negative15169
Negative (%)50.6%
Memory size234.5 KiB
2024-04-16T14:50:13.946934image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-6.3588877
5-th percentile-0.66552832
Q1-0.3835459
median-0.00085546875
Q30.33483789
95-th percentile0.62353418
Maximum11.271728
Range17.630615
Interquartile range (IQR)0.71838379

Descriptive statistics

Standard deviation0.74701547
Coefficient of variation (CV)-32.650751
Kurtosis36.672088
Mean-0.022878967
Median Absolute Deviation (MAD)0.36254883
Skewness-0.10904998
Sum-686.36902
Variance0.55803212
MonotonicityNot monotonic
2024-04-16T14:50:14.213818image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.005858398437 861
 
2.9%
0.01257226563 506
 
1.7%
-0.00085546875 355
 
1.2%
0.4422597656 295
 
1.0%
0.4355458984 278
 
0.9%
-0.4641123047 269
 
0.9%
0.4288320313 268
 
0.9%
-0.01428320312 266
 
0.9%
-0.4775400391 260
 
0.9%
0.4556875 249
 
0.8%
Other values (710) 26393
88.0%
ValueCountFrequency (%)
-6.358887695 1
 
< 0.1%
-6.338746094 1
 
< 0.1%
-6.332032227 4
< 0.1%
-6.318604492 1
 
< 0.1%
-6.311890625 4
< 0.1%
-6.305176758 3
< 0.1%
-6.291749023 1
 
< 0.1%
-6.285035156 4
< 0.1%
-6.278321289 1
 
< 0.1%
-6.271607422 3
< 0.1%
ValueCountFrequency (%)
11.27172754 1
 
< 0.1%
10.2780752 1
 
< 0.1%
7.908080078 1
 
< 0.1%
7.263548828 1
 
< 0.1%
7.149413086 1
 
< 0.1%
6.726439453 1
 
< 0.1%
6.713011719 1
 
< 0.1%
6.055052734 1
 
< 0.1%
6.048338867 2
< 0.1%
6.041625 3
< 0.1%

ib
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct710
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.025591695
Minimum-7.2644043
Maximum6.4385986
Zeros566
Zeros (%)1.9%
Negative13205
Negative (%)44.0%
Memory size234.5 KiB
2024-04-16T14:50:14.465076image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-7.2644043
5-th percentile-0.63110352
Q1-0.32897949
median0.020141602
Q30.3692627
95-th percentile0.66467285
Maximum6.4385986
Range13.703003
Interquartile range (IQR)0.69824219

Descriptive statistics

Standard deviation0.77052845
Coefficient of variation (CV)30.108535
Kurtosis35.458429
Mean0.025591695
Median Absolute Deviation (MAD)0.34912109
Skewness0.088247696
Sum767.75085
Variance0.59371409
MonotonicityNot monotonic
2024-04-16T14:50:14.747581image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.006713867188 796
 
2.7%
0 566
 
1.9%
0.01342773438 335
 
1.1%
0.4833984375 324
 
1.1%
0.4632568359 295
 
1.0%
0.4766845703 291
 
1.0%
0.4699707031 265
 
0.9%
0.4565429688 257
 
0.9%
0.4901123047 251
 
0.8%
0.02014160156 249
 
0.8%
Other values (700) 26371
87.9%
ValueCountFrequency (%)
-7.264404297 1
 
< 0.1%
-6.378173828 1
 
< 0.1%
-6.264038086 3
< 0.1%
-6.257324219 1
 
< 0.1%
-6.250610352 2
< 0.1%
-6.243896484 1
 
< 0.1%
-6.237182617 4
< 0.1%
-6.23046875 2
< 0.1%
-6.223754883 2
< 0.1%
-6.217041016 3
< 0.1%
ValueCountFrequency (%)
6.438598633 3
 
< 0.1%
6.431884766 8
< 0.1%
6.425170898 4
< 0.1%
6.418457031 3
 
< 0.1%
6.411743164 3
 
< 0.1%
6.405029297 1
 
< 0.1%
6.39831543 5
< 0.1%
6.391601562 3
 
< 0.1%
6.384887695 3
 
< 0.1%
6.378173828 1
 
< 0.1%

ic
Real number (ℝ)

HIGH CORRELATION 

Distinct726
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.048809062
Minimum-12.688359
Maximum6.352168
Zeros0
Zeros (%)0.0%
Negative16930
Negative (%)56.4%
Memory size234.5 KiB
2024-04-16T14:50:15.014077image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-12.688359
5-th percentile-0.66382324
Q1-0.34827148
median-0.059575195
Q30.2895459
95-th percentile0.58495605
Maximum6.352168
Range19.040527
Interquartile range (IQR)0.63781738

Descriptive statistics

Standard deviation0.74123904
Coefficient of variation (CV)-15.186505
Kurtosis40.948955
Mean-0.048809062
Median Absolute Deviation (MAD)0.30883789
Skewness0.056012913
Sum-1464.2719
Variance0.54943532
MonotonicityNot monotonic
2024-04-16T14:50:15.296978image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.3415576172 1731
 
5.8%
0.000849609375 806
 
2.7%
-0.005864257812 646
 
2.2%
-0.012578125 300
 
1.0%
-0.3482714844 273
 
0.9%
-0.4221240234 260
 
0.9%
0.4506787109 257
 
0.9%
-0.3952685547 246
 
0.8%
-0.33484375 245
 
0.8%
-0.4086962891 240
 
0.8%
Other values (716) 24996
83.3%
ValueCountFrequency (%)
-12.68835937 1
 
< 0.1%
-12.66821777 1
 
< 0.1%
-6.236333008 1
 
< 0.1%
-6.216191406 3
< 0.1%
-6.209477539 3
< 0.1%
-6.202763672 1
 
< 0.1%
-6.196049805 3
< 0.1%
-6.189335938 1
 
< 0.1%
-6.18262207 2
< 0.1%
-6.175908203 3
< 0.1%
ValueCountFrequency (%)
6.352167969 1
 
< 0.1%
6.345454102 3
< 0.1%
6.338740234 1
 
< 0.1%
6.332026367 2
< 0.1%
6.3253125 3
< 0.1%
6.318598633 2
< 0.1%
6.305170898 1
 
< 0.1%
6.298457031 3
< 0.1%
6.291743164 1
 
< 0.1%
6.285029297 2
< 0.1%

va
Real number (ℝ)

HIGH CORRELATION 

Distinct16389
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66328771
Minimum-159.03427
Maximum160.3241
Zeros0
Zeros (%)0.0%
Negative14924
Negative (%)49.7%
Memory size234.5 KiB
2024-04-16T14:50:15.567580image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-159.03427
5-th percentile-152.28378
Q1-109.2675
median1.0909271
Q3110.45486
95-th percentile153.98346
Maximum160.3241
Range319.35837
Interquartile range (IQR)219.72237

Descriptive statistics

Standard deviation109.92255
Coefficient of variation (CV)165.72378
Kurtosis-1.5028444
Mean0.66328771
Median Absolute Deviation (MAD)109.81598
Skewness0.0010671501
Sum19898.631
Variance12082.966
MonotonicityNot monotonic
2024-04-16T14:50:16.524424image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-154.7669983 17
 
0.1%
-154.5982361 15
 
0.1%
-154.4535828 13
 
< 0.1%
-152.6815796 13
 
< 0.1%
-154.6464539 13
 
< 0.1%
154.3450928 12
 
< 0.1%
-151.8016052 12
 
< 0.1%
-154.513855 11
 
< 0.1%
-153.8508606 11
 
< 0.1%
-152.5730896 11
 
< 0.1%
Other values (16379) 29872
99.6%
ValueCountFrequency (%)
-159.0342712 1
< 0.1%
-158.757019 1
< 0.1%
-158.6123657 1
< 0.1%
-158.1181335 1
< 0.1%
-157.8167725 1
< 0.1%
-157.1658325 1
< 0.1%
-156.7318726 1
< 0.1%
-156.6716003 1
< 0.1%
-156.5510559 2
< 0.1%
-156.5148926 1
< 0.1%
ValueCountFrequency (%)
160.3240967 1
< 0.1%
159.9986267 1
< 0.1%
159.5646667 1
< 0.1%
159.3235779 1
< 0.1%
159.0342712 1
< 0.1%
158.9498901 1
< 0.1%
158.9378357 1
< 0.1%
158.8534546 1
< 0.1%
158.8052368 1
< 0.1%
158.7931824 1
< 0.1%

vb
Real number (ℝ)

HIGH CORRELATION 

Distinct16399
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.025666
Minimum-159.21509
Maximum159.64905
Zeros1
Zeros (%)< 0.1%
Negative14919
Negative (%)49.7%
Memory size234.5 KiB
2024-04-16T14:50:16.760044image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-159.21509
5-th percentile-152.30789
Q1-108.936
median1.4585876
Q3111.26854
95-th percentile153.97141
Maximum159.64905
Range318.86414
Interquartile range (IQR)220.20454

Descriptive statistics

Standard deviation109.95615
Coefficient of variation (CV)107.20464
Kurtosis-1.502283
Mean1.025666
Median Absolute Deviation (MAD)110.13542
Skewness-0.0040707168
Sum30769.979
Variance12090.354
MonotonicityNot monotonic
2024-04-16T14:50:17.011344image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-152.1511841 14
 
< 0.1%
154.5620728 14
 
< 0.1%
154.5259094 13
 
< 0.1%
155.140686 12
 
< 0.1%
-152.8382874 12
 
< 0.1%
-155.0442505 12
 
< 0.1%
-151.741333 12
 
< 0.1%
-155.1045227 12
 
< 0.1%
154.6343994 12
 
< 0.1%
-152.6454163 12
 
< 0.1%
Other values (16389) 29875
99.6%
ValueCountFrequency (%)
-159.2150879 1
< 0.1%
-157.6118469 1
< 0.1%
-157.4069214 1
< 0.1%
-157.069397 1
< 0.1%
-156.6716003 1
< 0.1%
-156.5390015 1
< 0.1%
-156.4425659 1
< 0.1%
-156.418457 1
< 0.1%
-156.3702393 1
< 0.1%
-156.2376404 1
< 0.1%
ValueCountFrequency (%)
159.6490479 1
 
< 0.1%
158.9498901 1
 
< 0.1%
158.9378357 1
 
< 0.1%
158.865509 1
 
< 0.1%
158.7811279 1
 
< 0.1%
158.7449646 1
 
< 0.1%
158.7088013 1
 
< 0.1%
158.6846924 1
 
< 0.1%
158.6726379 1
 
< 0.1%
158.6605835 3
< 0.1%

vc
Real number (ℝ)

HIGH CORRELATION 

Distinct29634
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.74701479
Minimum-157.75248
Maximum159.20705
Zeros0
Zeros (%)0.0%
Negative14960
Negative (%)49.9%
Memory size234.5 KiB
2024-04-16T14:50:17.278229image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-157.75248
5-th percentile-152.39629
Q1-108.16452
median0.64290365
Q3109.84913
95-th percentile153.9917
Maximum159.20705
Range316.95953
Interquartile range (IQR)218.01365

Descriptive statistics

Standard deviation109.49546
Coefficient of variation (CV)146.57737
Kurtosis-1.4935522
Mean0.74701479
Median Absolute Deviation (MAD)109.00833
Skewness-0.00027159472
Sum22410.444
Variance11989.256
MonotonicityNot monotonic
2024-04-16T14:50:17.529092image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
154.1843669 4
 
< 0.1%
156.0487874 4
 
< 0.1%
-152.5168355 3
 
< 0.1%
151.87795 3
 
< 0.1%
-155.1889038 3
 
< 0.1%
149.402771 3
 
< 0.1%
154.6424357 3
 
< 0.1%
154.3008931 3
 
< 0.1%
-154.0035502 3
 
< 0.1%
154.8875427 3
 
< 0.1%
Other values (29624) 29968
99.9%
ValueCountFrequency (%)
-157.7524821 1
< 0.1%
-157.4913025 1
< 0.1%
-156.9327799 1
< 0.1%
-156.7358907 1
< 0.1%
-156.418457 1
< 0.1%
-156.3541667 1
< 0.1%
-156.3220215 1
< 0.1%
-156.2376404 1
< 0.1%
-156.2376404 1
< 0.1%
-156.2135315 1
< 0.1%
ValueCountFrequency (%)
159.2070516 1
< 0.1%
158.9539083 1
< 0.1%
158.9056905 1
< 0.1%
158.8896179 1
< 0.1%
158.8614909 1
< 0.1%
158.8574727 1
< 0.1%
158.8213094 1
< 0.1%
158.7610372 1
< 0.1%
158.7168376 1
< 0.1%
158.6927287 1
< 0.1%

Iabc
Real number (ℝ)

HIGH CORRELATION 

Distinct28777
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.61874144
Minimum1.222568 × 10-6
Maximum6.4608233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-04-16T14:50:17.779838image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.222568 × 10-6
5-th percentile0.011942301
Q10.45127648
median0.48464799
Q30.66913557
95-th percentile0.73440552
Maximum6.4608233
Range6.4608221
Interquartile range (IQR)0.21785909

Descriptive statistics

Standard deviation0.84731267
Coefficient of variation (CV)1.3694132
Kurtosis37.765892
Mean0.61874144
Median Absolute Deviation (MAD)0.043505312
Skewness6.1451558
Sum18562.243
Variance0.71793876
MonotonicityNot monotonic
2024-04-16T14:50:18.015059image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 59
 
0.2%
0.7075967432 3
 
< 0.1%
0.4801161501 3
 
< 0.1%
0.4572523799 3
 
< 0.1%
0.00137072389 3
 
< 0.1%
0.7083539293 3
 
< 0.1%
0.4272305419 3
 
< 0.1%
0.4432013615 3
 
< 0.1%
0.2638716339 3
 
< 0.1%
0.5165253137 3
 
< 0.1%
Other values (28767) 29914
99.7%
ValueCountFrequency (%)
1.222567992 × 10-61
< 0.1%
1.620265844 × 10-61
< 0.1%
2.316937515 × 10-61
< 0.1%
2.808569414 × 10-61
< 0.1%
4.76614446 × 10-61
< 0.1%
5.358318379 × 10-61
< 0.1%
8.414953649 × 10-61
< 0.1%
8.807365088 × 10-61
< 0.1%
9.134132889 × 10-61
< 0.1%
1.133165529 × 10-51
< 0.1%
ValueCountFrequency (%)
6.460823276 1
< 0.1%
6.460483635 1
< 0.1%
6.44365826 1
< 0.1%
6.418020237 1
< 0.1%
6.399898679 1
< 0.1%
6.384560663 1
< 0.1%
6.354807873 1
< 0.1%
6.273475091 1
< 0.1%
6.267955563 1
< 0.1%
6.256444267 1
< 0.1%

If_
Real number (ℝ)

Distinct28767
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.341476
Minimum-0.022218704
Maximum51.337426
Zeros0
Zeros (%)0.0%
Negative6
Negative (%)< 0.1%
Memory size234.5 KiB
2024-04-16T14:50:18.297636image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-0.022218704
5-th percentile48.632661
Q149.905288
median50.0051
Q350.113791
95-th percentile50.53935
Maximum51.337426
Range51.359645
Interquartile range (IQR)0.20850306

Descriptive statistics

Standard deviation4.9711429
Coefficient of variation (CV)0.10074978
Kurtosis71.371379
Mean49.341476
Median Absolute Deviation (MAD)0.10435556
Skewness-8.3284054
Sum1480244.3
Variance24.712262
MonotonicityNot monotonic
2024-04-16T14:50:18.580145image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 62
 
0.2%
49.9145329 3
 
< 0.1%
49.92754161 3
 
< 0.1%
50.04896798 3
 
< 0.1%
50.38689055 3
 
< 0.1%
49.94394714 3
 
< 0.1%
50.42858687 3
 
< 0.1%
50.0773956 3
 
< 0.1%
49.96205142 3
 
< 0.1%
50.13825823 3
 
< 0.1%
Other values (28757) 29911
99.7%
ValueCountFrequency (%)
-0.0222187038 1
< 0.1%
-0.01786698664 1
< 0.1%
-0.01747776866 1
< 0.1%
-0.005012716396 1
< 0.1%
-0.003130698867 1
< 0.1%
-0.002390377081 1
< 0.1%
0.005869051886 1
< 0.1%
0.01100721659 1
< 0.1%
0.01482723234 1
< 0.1%
0.01652575225 1
< 0.1%
ValueCountFrequency (%)
51.33742635 1
< 0.1%
51.33545458 1
< 0.1%
51.33007357 1
< 0.1%
51.3183812 1
< 0.1%
51.30815628 1
< 0.1%
51.29948733 1
< 0.1%
51.29692022 1
< 0.1%
51.29401749 1
< 0.1%
51.283629 1
< 0.1%
51.28139456 1
< 0.1%

Vabc
Real number (ℝ)

SKEWED 

Distinct28777
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.88709
Minimum1
Maximum156.26828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-04-16T14:50:18.831003image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile154.78801
Q1154.97941
median155.24697
Q3155.44642
95-th percentile155.71433
Maximum156.26828
Range155.26828
Interquartile range (IQR)0.46701317

Descriptive statistics

Standard deviation6.9538026
Coefficient of variation (CV)0.044895947
Kurtosis471.3494
Mean154.88709
Median Absolute Deviation (MAD)0.23192118
Skewness-21.580826
Sum4646612.7
Variance48.35537
MonotonicityNot monotonic
2024-04-16T14:50:19.129136image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 59
 
0.2%
155.4635622 3
 
< 0.1%
155.5219852 3
 
< 0.1%
155.667414 3
 
< 0.1%
155.3071664 3
 
< 0.1%
155.0598984 3
 
< 0.1%
154.5882033 3
 
< 0.1%
155.3751938 3
 
< 0.1%
155.2482909 3
 
< 0.1%
155.0053613 3
 
< 0.1%
Other values (28767) 29914
99.7%
ValueCountFrequency (%)
1 59
0.2%
69.60377345 1
 
< 0.1%
72.23811249 1
 
< 0.1%
80.11885473 1
 
< 0.1%
95.03876285 1
 
< 0.1%
97.54459705 1
 
< 0.1%
105.3740581 1
 
< 0.1%
110.6101513 1
 
< 0.1%
113.7889051 1
 
< 0.1%
115.7653297 1
 
< 0.1%
ValueCountFrequency (%)
156.2682826 1
< 0.1%
156.2535008 1
< 0.1%
156.2346373 1
< 0.1%
156.2272736 1
< 0.1%
156.2046285 1
< 0.1%
156.203587 1
< 0.1%
156.1978685 1
< 0.1%
156.1907714 1
< 0.1%
156.1901175 1
< 0.1%
156.1845283 1
< 0.1%

Vf
Real number (ℝ)

Distinct28768
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.999756
Minimum49.492334
Maximum50.461928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size234.5 KiB
2024-04-16T14:50:19.426763image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum49.492334
5-th percentile49.977433
Q149.995819
median50.000088
Q350.004349
95-th percentile50.021654
Maximum50.461928
Range0.96959398
Interquartile range (IQR)0.0085305621

Descriptive statistics

Standard deviation0.023231527
Coefficient of variation (CV)0.00046463281
Kurtosis101.64506
Mean49.999756
Median Absolute Deviation (MAD)0.0042665705
Skewness-2.603007
Sum1499992.7
Variance0.00053970386
MonotonicityNot monotonic
2024-04-16T14:50:19.709286image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 62
 
0.2%
50.00442031 3
 
< 0.1%
50.01674236 3
 
< 0.1%
50.00050257 3
 
< 0.1%
49.99595793 3
 
< 0.1%
50.00263316 3
 
< 0.1%
50.00887356 3
 
< 0.1%
50.00075612 3
 
< 0.1%
50.00339564 3
 
< 0.1%
50.00014173 3
 
< 0.1%
Other values (28758) 29911
99.7%
ValueCountFrequency (%)
49.49233366 1
< 0.1%
49.50624882 1
< 0.1%
49.57328169 1
< 0.1%
49.57328488 1
< 0.1%
49.57370432 1
< 0.1%
49.57455255 1
< 0.1%
49.57964316 1
< 0.1%
49.6033658 1
< 0.1%
49.60676045 1
< 0.1%
49.61083949 1
< 0.1%
ValueCountFrequency (%)
50.46192764 1
< 0.1%
50.46065026 1
< 0.1%
50.41673832 1
< 0.1%
50.41369863 1
< 0.1%
50.35210239 1
< 0.1%
50.34832909 1
< 0.1%
50.34519885 1
< 0.1%
50.33956904 1
< 0.1%
50.31119827 1
< 0.1%
50.31109796 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size234.5 KiB
1
20000 
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters30000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 20000
66.7%
0 10000
33.3%

Length

2024-04-16T14:50:19.928879image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T14:50:20.117220image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
ValueCountFrequency (%)
1 20000
66.7%
0 10000
33.3%

Most occurring characters

ValueCountFrequency (%)
1 20000
66.7%
0 10000
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20000
66.7%
0 10000
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 30000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20000
66.7%
0 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20000
66.7%
0 10000
33.3%

Interactions

2024-04-16T14:50:08.157898image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:33.796350image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:36.478609image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:38.989541image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:41.466740image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:44.302572image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:46.856513image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:49.384083image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:52.112597image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:54.739260image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:57.285608image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:00.517425image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:03.058787image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:05.521977image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:08.330610image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:34.000316image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:36.682962image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:39.161742image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:41.651580image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:44.506557image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:47.029230image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:49.571421image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:52.290428image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:54.942727image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:57.473954image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:00.708392image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:03.231498image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:05.725949image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:08.487303image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:34.188665image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:36.855283image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:39.318441image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:41.808155image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:44.694893image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:47.201945image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:49.728502image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:52.473269image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:55.110765image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:57.677921image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:00.878095image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:03.403815image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:05.897766image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:08.660014image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:34.392137image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:37.012370image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:39.475515image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:41.996498image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:44.874215image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:47.379658image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:49.916335image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:52.645974image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:55.288987image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:57.850631image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:01.050816image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:03.560892image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:06.086122image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:08.848368image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:34.580472image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:37.185082image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:39.663855image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:42.153179image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:45.055540image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:47.547354image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:50.073025image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:52.834315image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:55.446075image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:58.603615image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:01.223522image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:03.714966image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:06.258838image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:09.004545image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:34.784440image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:37.373414image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:39.851806image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:42.310263image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:45.228266image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:47.720069image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:50.245727image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:53.053916image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:55.634413image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:58.807601image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:01.409857image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:03.890298image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:06.463207image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:09.192878image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:34.952638image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:37.561766image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:40.024509image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:42.482971image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:45.400477image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:47.924036image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:50.434065image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:53.224887image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:55.838395image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:59.011567image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:01.584187image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:04.062511image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:06.635911image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:09.381227image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:35.129465image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:37.758725image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:40.197220image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:42.655287image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:45.575796image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:48.112371image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:50.606777image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:53.405619image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:56.011107image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:59.231185image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:01.772525image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:04.250864image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:06.824256image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:09.553941image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:35.333436image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:37.938050image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:40.385553image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:42.827991image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:45.761127image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:48.285090image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:50.795110image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:53.593959image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:56.183428image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:59.405511image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:01.960865image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:04.423570image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:07.043853image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:09.728261image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:35.506145image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:38.110760image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:40.557865image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:43.016329image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:45.933832image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:48.457407image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:50.983062image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:53.781909image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:56.371767image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:59.576216image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:02.133585image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:04.617036image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:07.247833image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:09.898958image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:35.694487image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:38.283470image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:40.730572image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:43.173406image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:46.122179image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:48.630116image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:51.188035image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:53.970249image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:56.548755image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:59.748931image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:02.311911image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:04.799871image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:07.423160image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:10.087298image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:35.882828image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:38.471805image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:40.903295image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:43.370866image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:46.310516image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:48.818454image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:51.391385image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:54.194362image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:56.737104image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:59.937276image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:02.478115image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:04.988212image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:07.624509image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:10.275640image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:36.070666image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:38.644121image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:41.091134image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:43.941526image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:46.480732image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:49.006793image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:51.657878image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:54.378207image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:56.909310image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:00.125613image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:02.666464image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:05.160924image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:07.796829image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:10.448348image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:36.259009image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:38.832456image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:41.279467image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:44.114231image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:46.684704image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:49.210766image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:51.889486image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:54.550912image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:49:57.113285image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:00.329594image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:02.886079image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:05.364903image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-04-16T14:50:07.985183image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Correlations

2024-04-16T14:50:20.276166image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Defective_Non_DefectiveIabcIf_IpvTimeVabcVdcVfVpviaibicvavbvc
Defective_Non_Defective1.000-0.408-0.004-0.253-0.0880.139-0.1360.0050.281-0.0250.047-0.026-0.0000.0010.004
Iabc-0.4081.0000.0500.456-0.2320.0740.5630.032-0.5310.031-0.0200.0630.0070.007-0.007
If_-0.0040.0501.000-0.119-0.091-0.0700.0200.0630.132-0.0090.008-0.050-0.008-0.0030.014
Ipv-0.2530.456-0.1191.0000.077-0.1570.270-0.013-0.8410.012-0.0420.0600.002-0.002-0.012
Time-0.088-0.232-0.0910.0771.0000.008-0.3670.000-0.082-0.0120.004-0.095-0.0100.0020.005
Vabc0.1390.074-0.070-0.1570.0081.0000.0520.085-0.046-0.011-0.007-0.0090.0120.0200.003
Vdc-0.1360.5630.0200.270-0.3670.0521.0000.004-0.2900.0100.0440.0370.039-0.0390.008
Vf0.0050.0320.063-0.0130.0000.0850.0041.000-0.010-0.0030.019-0.0180.005-0.0180.016
Vpv0.281-0.5310.132-0.841-0.082-0.046-0.290-0.0101.000-0.0060.044-0.064-0.0090.0010.003
ia-0.0250.031-0.0090.012-0.012-0.0110.010-0.003-0.0061.000-0.485-0.443-0.8800.4720.414
ib0.047-0.0200.008-0.0420.004-0.0070.0440.0190.044-0.4851.000-0.4440.434-0.8760.456
ic-0.0260.063-0.0500.060-0.095-0.0090.037-0.018-0.064-0.443-0.4441.0000.4520.374-0.835
va-0.0000.007-0.0080.002-0.0100.0120.0390.005-0.009-0.8800.4340.4521.000-0.492-0.472
vb0.0010.007-0.003-0.0020.0020.020-0.039-0.0180.0010.472-0.8760.374-0.4921.000-0.480
vc0.004-0.0070.014-0.0120.0050.0030.0080.0160.0030.4140.456-0.835-0.472-0.4801.000

Missing values

2024-04-16T14:50:10.699206image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-16T14:50:11.216435image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimeIpvVpvVdciaibicvavbvcIabcIf_VabcVfDefective_Non_Defective
08.4916641.544891101.300049142.9687500.381835-0.4901120.094844-110.466919150.391235-39.6792090.46514250.185838154.75145049.9951630
12.9460392.32064890.728760146.7773440.0394280.584106-0.670537-5.605316-130.718384136.9304400.66900849.907602154.87294250.0019870
26.0594311.536377101.623535142.9687500.3012690.134277-0.381841-113.673401-30.859375147.3615520.44771249.934645154.89202150.0082621
30.7622622.37362788.256836147.3632810.2408440.429688-0.636968-69.505920-84.935608154.3250020.69077850.330598154.80365949.9937441
40.6013782.28659188.409424147.6562500.4758290.187988-0.663823-106.067047-46.361389150.9698490.69924449.948302155.07159250.0041861
59.5959231.472046100.793457142.382812-0.4708260.684814-0.173711125.643463-142.49557519.5844520.49091149.872905154.86344249.9973821
65.9936811.340546102.197266143.554688-0.0679940.429688-0.32813036.175385-147.040100115.3047690.44078849.932418155.30709349.9973701
713.2019052.5855412.5939941.1718750.0058580.0000000.000850-83.260040-68.842926155.9161890.00317747.556789155.31550650.0011571
86.2971841.481506101.342773142.9687500.3146960.167847-0.475835-89.456024-63.755951154.1522220.49300149.984356154.85780650.0013010
92.3523982.25347990.222168147.949219-0.6990980.0738530.511104146.292725-22.095795-120.3957620.72371750.021015155.63504650.0009950
TimeIpvVpvVdciaibicvavbvcIabcIf_VabcVfDefective_Non_Defective
2999011.0618332.20239391.668701147.0703120.677245-0.255127-0.462407-151.36764551.484528104.1463720.72698850.072381155.28388050.0055040
299915.0406751.529755101.342773144.4335940.1535630.322266-0.455693-40.153351-107.742615151.2270100.43678050.466100155.10680949.9572471
299924.6025642.37835787.988281148.5351560.2341300.456543-0.670537-52.509155-94.759979156.3139850.74500749.993563155.62786749.9980041
299936.9332302.28375288.293457147.363281-0.155274-0.5303960.65880923.457947119.736786-145.6056210.71166549.795424155.07950450.0068341
299944.9324731.385010101.800537143.8476560.079711-0.4699710.403682-44.842529151.464081-106.1554460.46342149.793551155.27282350.0036741
299953.0353142.27334687.188721147.0703120.348266-0.6713870.316401-74.110718153.971405-81.5442910.66307050.216318154.99644050.0119691
299960.3945981.448395101.373291144.1406250.435546-0.4766850.047847-110.768280149.909058-40.3743490.50929750.163328155.16806350.0085201
299972.8886442.31781090.399170147.070312-0.4641120.691528-0.247563109.466400-150.53588941.8771360.69165849.856226154.98809550.0089750
299980.9451341.495697100.988770144.140625-0.5178230.1275630.363398148.088837-34.873505-113.5970560.50173150.058510154.93631149.9992780
299993.1225052.55715987.957764147.6562500.2475580.422974-0.636968-57.318878-93.783569154.1200760.67141149.954470155.22665149.9771581